Tom Nigro is Chief Operating Officer at GTCOM-US, an alternative data fintech firm. 

All industries underwent disruption in 2020. What do you think will be top of mind for investors in 2021 as the financial sector continues to weather the pandemic storm?

Trends we’ve seen during the pandemic, such as a boost in e-commerce, remote work and an emphasis on online education, will continue to be top of mind across the financial industry as the pandemic hopefully begins to plateau following vaccination efforts.

As businesses continue to adapt, data-driven investors and analysts will be looking to increase the sheer amount of information they’re using in order to identify value in the market in 2021. Tapping into advanced technology and data – using things like AI, machine learning and advanced NLP – is becoming more mainstream than ever before. We’re seeing that investing strategies based on traditional methods alone are no longer enough to differentiate a portfolio. That’s why alternative data is so powerful when it comes to driving alpha, as the signals extracted can help investors access unique, much deeper insights on their markets.

How have you seen market appetite change when it comes to investing into Asia?

The biggest change I have seen this year is that what was previously untapped and thought of as a foreign market has been pushed to the forefront of investors’ minds. There has been an influx of investment from the US into Asia which has been great to see – in no small part driven by the opening up of China’s financial markets to global investors, and the way in which China has experienced a strong recovery from COVID-19.

Investors are becoming more open to investing in Asia as they have access to insights that create a clearer picture for them to use in their trading strategies. Data-driven portfolios, comprising of alternative data rather than traditional market data alone, are now driving an increased flow of investment from the West into the East.

What kind of alternative data have investors been looking for in 2020, and how do you anticipate their needs will change in 2021?

Payment flow data, particularly credit card transaction data, is incredibly popular at the moment. Because payment data has a strong ability to predict overall revenue, and therefore business performance, this type of data is in high demand. As we enter 2021, we can expect to see increased demand for payment data from China. This will become even more important to investors given the impact of China’s market on the overall revenue of various large global retail brands. Online e-commerce data is easier to access, and on top of that investors already have increasing access to offline payment data from other regions such as the US and the UK.  However, offline in-store payment data from China has historically been difficult to source. Given China is a crucial region to factor in when it comes to accurate global revenue predictions, we can expect to see increased demand for credit card data covering offline payments in 2021 as investors look to complete this global picture.

What other market trends have you seen in the last year that you expect to be prominent in 2021?

Broadly, trends I expect to see in 2021 include greater access to liquidity in emerging markets such Asia and Africa, as well as a continued warming up to ESG investments as the millennial investor gains more market share and looks to make an impact.

When it comes to accessing the emerging markets, it will be increasingly important for investors to find clear and simple ways to extract signals from data which help them to genuinely generate alpha. For investments into China in particular, a key way to do this is by using sentiment data, which analyses sentiment trends regarding specific companies, sectors or thematic issues. We’re seeing huge demand for this type of daily updated data, which provides sentiment insights pulled from a huge range of alternative online sources in China, including news sites, forums and social channels such as Twitter, Facebook, WeChat and Weibo.